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Metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the GMrepo database

BACKGROUND: Previous evidence has shown that the gut microbiota plays a role in the development and progression of colorectal cancer (CRC). This study aimed to provide quantitative analysis and visualization of the interaction between the gut microbiota and CRC in order to establish a more precise m...

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Autores principales: Chen, Han, Jiao, Jianhua, Wei, Min, Jiang, Xingzhou, Yang, Ruoyun, Yu, Xin, Zhang, Guoxin, Zhou, Xiaoying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784093/
https://www.ncbi.nlm.nih.gov/pubmed/36564826
http://dx.doi.org/10.1186/s13099-022-00527-8
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author Chen, Han
Jiao, Jianhua
Wei, Min
Jiang, Xingzhou
Yang, Ruoyun
Yu, Xin
Zhang, Guoxin
Zhou, Xiaoying
author_facet Chen, Han
Jiao, Jianhua
Wei, Min
Jiang, Xingzhou
Yang, Ruoyun
Yu, Xin
Zhang, Guoxin
Zhou, Xiaoying
author_sort Chen, Han
collection PubMed
description BACKGROUND: Previous evidence has shown that the gut microbiota plays a role in the development and progression of colorectal cancer (CRC). This study aimed to provide quantitative analysis and visualization of the interaction between the gut microbiota and CRC in order to establish a more precise microbiota panel for CRC diagnosis. METHOD: A paired-sample study was designed by retrieving original metagenomic data from the GMrepo database. The differences in the distribution of the gut microbiota between CRCs and controls were analysed at the species level. A co-occurrence network was established, and the microbial interactions with environmental factors were assessed. Random forest models were used to determine significant biomarkers for differentiating CRC and control samples. RESULTS: A total of 709 metagenomic samples from 6 projects were identified. After matching, 86 CRC patients and 86 matched healthy controls from six countries were enrolled. A total of 484 microbial species and 166 related genera were analysed. In addition to previously recognized associations between Fusobacterium nucleatum and species belonging to the genera Peptostreptococcus, Porphyromonas, and Prevotella and CRC, we found new associations with the novel species of Parvimonas micra and Collinsella tanakaei. In CRC patients, Bacteroides uniformis and Collinsella tanakaei were positively correlated with age, whereas Dorea longicatena, Adlercreutzia equolifaciens, and Eubacterium hallii had positive associations with body mass index (BMI). Finally, a random forest model was established by integrating different numbers of species with the highest model-building importance and lowest inner subcategory bias. The median value of the area under the receiver operating characteristic curve (AUC) was 0.812 in the training cohort and 0.790 in the validation set. CONCLUSIONS: Our study provides a novel bioinformatics approach for investigating the interaction between the gut microbiota and CRC using an online free database. The identification of key species and their associated genes should be further emphasized to determine the relative causality of microbial organisms in the development of CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13099-022-00527-8.
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spelling pubmed-97840932022-12-24 Metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the GMrepo database Chen, Han Jiao, Jianhua Wei, Min Jiang, Xingzhou Yang, Ruoyun Yu, Xin Zhang, Guoxin Zhou, Xiaoying Gut Pathog Research BACKGROUND: Previous evidence has shown that the gut microbiota plays a role in the development and progression of colorectal cancer (CRC). This study aimed to provide quantitative analysis and visualization of the interaction between the gut microbiota and CRC in order to establish a more precise microbiota panel for CRC diagnosis. METHOD: A paired-sample study was designed by retrieving original metagenomic data from the GMrepo database. The differences in the distribution of the gut microbiota between CRCs and controls were analysed at the species level. A co-occurrence network was established, and the microbial interactions with environmental factors were assessed. Random forest models were used to determine significant biomarkers for differentiating CRC and control samples. RESULTS: A total of 709 metagenomic samples from 6 projects were identified. After matching, 86 CRC patients and 86 matched healthy controls from six countries were enrolled. A total of 484 microbial species and 166 related genera were analysed. In addition to previously recognized associations between Fusobacterium nucleatum and species belonging to the genera Peptostreptococcus, Porphyromonas, and Prevotella and CRC, we found new associations with the novel species of Parvimonas micra and Collinsella tanakaei. In CRC patients, Bacteroides uniformis and Collinsella tanakaei were positively correlated with age, whereas Dorea longicatena, Adlercreutzia equolifaciens, and Eubacterium hallii had positive associations with body mass index (BMI). Finally, a random forest model was established by integrating different numbers of species with the highest model-building importance and lowest inner subcategory bias. The median value of the area under the receiver operating characteristic curve (AUC) was 0.812 in the training cohort and 0.790 in the validation set. CONCLUSIONS: Our study provides a novel bioinformatics approach for investigating the interaction between the gut microbiota and CRC using an online free database. The identification of key species and their associated genes should be further emphasized to determine the relative causality of microbial organisms in the development of CRC. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13099-022-00527-8. BioMed Central 2022-12-23 /pmc/articles/PMC9784093/ /pubmed/36564826 http://dx.doi.org/10.1186/s13099-022-00527-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Chen, Han
Jiao, Jianhua
Wei, Min
Jiang, Xingzhou
Yang, Ruoyun
Yu, Xin
Zhang, Guoxin
Zhou, Xiaoying
Metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the GMrepo database
title Metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the GMrepo database
title_full Metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the GMrepo database
title_fullStr Metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the GMrepo database
title_full_unstemmed Metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the GMrepo database
title_short Metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the GMrepo database
title_sort metagenomic analysis of the interaction between the gut microbiota and colorectal cancer: a paired-sample study based on the gmrepo database
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9784093/
https://www.ncbi.nlm.nih.gov/pubmed/36564826
http://dx.doi.org/10.1186/s13099-022-00527-8
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